IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v42y2022i10p1797-1820.html
   My bibliography  Save this article

Margin requirements based on a stochastic correlation model

Author

Listed:
  • Dávid Zoltán Szabó
  • Kata Váradi

Abstract

We demonstrate that margin requirements of central counterparties show a significantly different behavior when calculated with a portfoliowise treatment instead of taking the weighted sum of the margin requirements of the components without accounting for their correlation structures. This is shown via simulating trajectories of a joint stochastic volatility–stochastic correlation model. Results indicate that an unnecessarily large overmargin requirement is set by regulators when the applied risk measure is not calculated via a portfoliowise treatment. Finally, accounting for the correlation structure of the assets during the margining process would not lead to an overly prudent method, nor would it cause greater procyclicality.

Suggested Citation

  • Dávid Zoltán Szabó & Kata Váradi, 2022. "Margin requirements based on a stochastic correlation model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1797-1820, October.
  • Handle: RePEc:wly:jfutmk:v:42:y:2022:i:10:p:1797-1820
    DOI: 10.1002/fut.22360
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22360
    Download Restriction: no

    File URL: https://libkey.io/10.1002/fut.22360?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Bakoush, Mohamed & Gerding, Enrico H. & Wolfe, Simon, 2019. "Margin requirements and systemic liquidity risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 78-95.
    2. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    3. Radoslav Raykov, 2014. "Optimal Margining and Margin Relief in Centrally Cleared Derivatives Markets," Staff Working Papers 14-29, Bank of Canada.
    4. Daniel Heller & Nicholas Vause, 2012. "Collateral requirements for mandatory central clearing of over-the-counter derivatives," BIS Working Papers 373, Bank for International Settlements.
    5. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    6. Markus K. Brunnermeier & Lasse Heje Pedersen, 2009. "Market Liquidity and Funding Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2201-2238, June.
    7. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
    8. Jennifer Hancock & David Hughes & Suchita Mathur, 2016. "Sources of Financial Risk for Central Counterparties," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 69-76, September.
    9. Murphy, David & Vasios, Michalis & Vause, Nick, 2014. "Financial Stability Paper No 29: An investigation into the procyclicality of risk-based initial margin models," Bank of England Financial Stability Papers 29, Bank of England.
    10. Paul Glasserman & Qi Wu, 2018. "Persistence and Procyclicality in Margin Requirements," Management Science, INFORMS, vol. 64(12), pages 5705-5724, December.
    11. Chesney, Marc & Scott, Louis, 1989. "Pricing European Currency Options: A Comparison of the Modified Black-Scholes Model and a Random Variance Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(3), pages 267-284, September.
    12. László Márkus & Ashish Kumar, 2021. "Modelling Joint Behaviour of Asset Prices Using Stochastic Correlation," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 341-354, March.
    13. Kastner, Gregor, 2016. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i05).
    14. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    15. Xue-Zhong He & Eva Lütkebohmert & Yajun Xiao, 2017. "Rollover risk and credit risk under time-varying margin," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 455-469, March.
    16. Robert Cox & Richard Heckinger & David A. Marshall, 2016. "Cleared Margin Setting at Selected Central Counterparties," Economic Perspectives, Federal Reserve Bank of Chicago, issue 4.
    17. Murphy, David & Vasios, Michalis & Vause, Nicholas, 2016. "A comparative analysis of tools to limit the procyclicality of initial margin requirements," Bank of England working papers 597, Bank of England.
    18. Yang-Ho Park & Nicole Abruzzo, 2016. "An Empirical Analysis of Futures Margin Changes: Determinants and Policy Implications," Journal of Financial Services Research, Springer;Western Finance Association, vol. 49(1), pages 65-100, February.
    19. Dietrich Domanski & Leonardo Gambacorta & Cristina Picillo, 2015. "Central clearing: trends and current issues," BIS Quarterly Review, Bank for International Settlements, December.
    20. Daníelsson, Jón & Jorgensen, Bjørn N. & Samorodnitsky, Gennady & Sarma, Mandira & de Vries, Casper G., 2013. "Fat tails, VaR and subadditivity," Journal of Econometrics, Elsevier, vol. 172(2), pages 283-291.
    21. David Longworth, 2010. "Warding Off Financial Market Failure: How to Avoid Squeezed Margins and Bad Haircuts," C.D. Howe Institute Backgrounder, C.D. Howe Institute, issue 135, December.
    22. Ms. Laura Valderrama, 2010. "Macroprudential Regulation Under Repo Funding," IMF Working Papers 2010/220, International Monetary Fund.
    23. Vicente, L.A.B.G. & Cerezetti, F.V. & De Faria, S.R. & Iwashita, T. & Pereira, O.R., 2015. "Managing risk in multi-asset class, multimarket central counterparties: The CORE approach," Journal of Banking & Finance, Elsevier, vol. 51(C), pages 119-130.
    24. Murphy, David & Vause, Nicholas, 2021. "A CBA of APC: analysing approaches to procyclicality reduction in CCP initial margin models," Bank of England working papers 950, Bank of England.
    25. Elena Goldman & Xiangjin Shen, 2018. "Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement," Staff Working Papers 18-21, Bank of Canada.
    26. Ron Berndsen, 2021. "Fundamental questions on central counterparties: A review of the literature," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2009-2022, December.
    27. Bakoush, Mohamed & Gerding, Enrico H. & Wolfe, Simon, 2020. "Interest rate swaps clearing and systemic risk," Finance Research Letters, Elsevier, vol. 33(C).
    28. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
    29. Berlinger, Edina & Dömötör, Barbara & Illés, Ferenc, 2019. "Optimal margin requirement," Finance Research Letters, Elsevier, vol. 31(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alexander, Carol & Kaeck, Andreas & Sumawong, Anannit, 2019. "A parsimonious parametric model for generating margin requirements for futures," European Journal of Operational Research, Elsevier, vol. 273(1), pages 31-43.
    2. Corradin, Stefano & Heider, Florian & Hoerova, Marie, 2017. "On collateral: implications for financial stability and monetary policy," Working Paper Series 2107, European Central Bank.
    3. Nikil Chande & Nicholas Labelle, 2016. "Using Speed and Credit Limits to Address the Procyclicality of Initial Margin at Central Counterparties," Discussion Papers 16-18, Bank of Canada.
    4. Berlinger, Edina & Dömötör, Barbara & Illés, Ferenc, 2019. "Anti-cyclical versus risk-sensitive margin strategies in central clearing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 117-131.
    5. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    6. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689.
    7. Lannoo, Karel & Thomadakis, Apostolos, 2020. "Derivatives in Sustainable Finance," ECMI Papers 29791, Centre for European Policy Studies.
    8. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
    9. Qiang Zhang & Rui Luo & Yaodong Yang & Yuanyuan Liu, 2018. "Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series," Papers 1811.03711, arXiv.org.
    10. Yu, Jun, 2005. "On leverage in a stochastic volatility model," Journal of Econometrics, Elsevier, vol. 127(2), pages 165-178, August.
    11. Rui Luo & Weinan Zhang & Xiaojun Xu & Jun Wang, 2017. "A Neural Stochastic Volatility Model," Papers 1712.00504, arXiv.org, revised Dec 2018.
    12. Yu, Jun & Yang, Zhenlin & Zhang, Xibin, 2006. "A class of nonlinear stochastic volatility models and its implications for pricing currency options," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2218-2231, December.
    13. Huber, Florian & Rabitsch, Katrin, 2019. "Exchange rate dynamics and monetary policy - Evidence from a non-linear DSGE-VAR approach," Department of Economics Working Paper Series 295, WU Vienna University of Economics and Business.
    14. Murphy, David & Vause, Nicholas, 2021. "A CBA of APC: analysing approaches to procyclicality reduction in CCP initial margin models," Bank of England working papers 950, Bank of England.
    15. Hitoshi Hayakawa, 2018. "Does a central clearing counterparty reduce liquidity needs?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 9-50, April.
    16. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    17. Siem Jan Koopman & Eugenie Hol Uspensky, 2000. "The Stochastic Volatility in Mean Model," Tinbergen Institute Discussion Papers 00-024/4, Tinbergen Institute.
    18. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
    19. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    20. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jfutmk:v:42:y:2022:i:10:p:1797-1820. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.